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IT & Software Other IT & Software Python

Learn programming from scratch with Python

learn software programming starting from No Knowledge with the most powerful and popular programming language, python
Rating: 4.1 out of 54.1 (69 ratings)
13,572 students
Created by Daniele Protti
Last updated 11/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • software programming and coding
  • Program software with Python
  • know how to develop software in Python

Requirements

  • Use PC or MAC

Description

Whether you are an experienced programmer or not, this course is intended for everyone who wishes to learn the Python programming language.

This course outlines the process from learning the basis of programming with Python and start writing your own code.

Python is a powerful general-purpose programming language

It is used in web development, data science, creating software prototypes, and so on.

It is so powerful and easy that it is recommended to whom wants to start learning software programming even with no experience and knowledge.

In this course students will learn:

  • How to install and run Python on your computer and write your first Python program

  • keywords (reserved words in Python) and identifiers (names given to variables, functions, etc.)

  • Python statements, why indentation is important and use of comments in programming

  • Python variables, constants, literals and their use cases

  • Type conversion and uses of type conversion

  • Python Operators

  • Python Namespaces

  • print() and input() to perform I/O tasks in Python

  • Python Data Types (Python Numbers, Python List, Python Tuple, Python String, Python Set, Python Dictionary)

  • Flow Control (IF Statements, Loops – For, While,…)

  • Functions (Function Argument, Python Recursion, Anonymous Function, Global, Local and Nonlocal, Python Global Keyword, Python Modules,Python Package)

  • Manage Files (Python File Operation, Python Directory, Python Exception, Exception Handling, User-defined Exception)

  • Python Object Oriented Programming (OOP) (Python OOP, Python Objects & Classes, Python Inheritance, Multiple Inheritance, Encapsulation, Polymorphism, Operator Overloading)

  • Advanced Functionalities (Python Iterator, Python Generator, Python Closure, Python Decorators, Python Property, Python RegEx, Serialization, Special Functions)

  • Data Science Applications (Numpy, Pandas)


Everything enriched by exercises, applications and special bonuses to learn how to write optimized software code


Who this course is for:

  • Future software developers
  • Data Analysts
  • Software project managers
  • Software architects

Course content

13 sections • 135 lectures • 11h 21m total length

  • Preview05:08
  • Why You Want To Learn Programming?
    05:23
  • Pick a Programming Language To Learn
    03:18
  • Why should you pick up and learn Python
    12:37
  • Learn In Small Chunks
    03:35
  • Start At The Beginning
    01:44
  • Learn and Teach
    04:25
  • Do not give up
    06:41
  • Should I learn programming if I don’t want to be a programmer?
    03:11

  • Preview03:09
  • Install Python
    01:56
  • Run Python in Immediate mode
    02:08
  • Run Python in the Integrated Development Environment (IDE)
    02:25
  • A first Python Program
    01:25

  • Python Keywords
    02:06
  • Statements & Comments
    06:24
  • Docstrings
    02:49
  • Python Variables & Constants
    07:21
  • Python Literals
    07:01
  • Python Datatypes
    11:51
  • Python Type Conversion (I)
    04:40
  • Python Type Conversion (II)
    05:44
  • Python I/O: print
    08:21
  • Python I/O: input
    03:32
  • Python Import
    05:26
  • Python Operators
    04:25
  • Python Namespace (I)
    04:19
  • Python Namespace (II)
    03:54
  • Python Namespace (III)
    05:31
  • Python Namespace (IV)
    03:31

  • Preview03:16
  • Python if...else (Ii)
    02:52
  • Python if...else (III)
    03:13
  • Python if...else (IV)
    04:44
  • Python for Loop
    06:47
  • Python while Loop
    03:17
  • Python break and continue
    04:20
  • Python Pass
    01:52

  • Python Functions
    05:47
  • Function Argument
    05:57
  • Python Recursion
    03:00
  • Anonymous Function
    06:01
  • Python Global, Local and Nonlocal variables
    10:41
  • Python Global Keyword
    09:09
  • Python Modules
    07:54
  • Python Package
    02:31

  • Python Numbers
    11:00
  • Python List (I)
    07:08
  • Python List (II)
    10:38
  • Python Tuple (I)
    05:23
  • Python Tuple (II)
    06:35
  • Python String (I)
    04:55
  • Python String (II)
    04:03
  • Python String (III)
    04:30
  • Python String (IV)
    02:58
  • Python Set (I)
    07:33
  • Python Set (II)
    04:24
  • Python Dictionary
    08:07

  • Python File Operation (I)
    08:43
  • Python File Operation (II)
    07:37
  • Python Directory
    07:55
  • Python Exception
    06:40
  • Python Exception Handling (I)
    04:14
  • Python Exception Handling (II)
    03:15
  • Python Exception Handling (III)
    01:53
  • Python Exception Handling (IV)
    01:44
  • Python User-defined Exception
    10:04

  • Python OOP
    02:07
  • Python OOP: Classes and Objects (I)
    06:25
  • Python OOP: Classes and Objects (II)
    02:42
  • Python OPP: Classes: definition
    07:09
  • Python OPP: Classes: initialization (I)
    02:03
  • Python OPP: Classes: initialization (II)
    06:31
  • Python OOP: inheritance (I)
    04:31
  • Python OOP: inheritance (II)
    12:32
  • Pythin OOP: Multiple Inheritance
    06:02
  • Python OOP: encapsulation
    04:55
  • Python OOP: polymorphism
    03:56
  • Operator Overloading (I)
    05:01
  • Operator Overloading (II)
    05:19
  • Operator Overloading (III)
    04:14

  • Python Iterator
    08:48
  • Python Custom Iterator
    06:36
  • Python Infinite Iterators
    03:51
  • Python Generator
    08:11
  • Python Generator Expressions
    05:11
  • Advantages of using Generators
    04:18
  • Python Closure
    07:21
  • Python Decorators
    08:42
  • Python Decorators: decorators with parameters
    04:22
  • Python Decorators: chaning decorators
    02:24
  • Python @Property
    04:11
  • Getter and Setter Methods
    06:06
  • @Property Class
    04:32
  • Python @Property Decorator
    05:09
  • Python RegEx
    08:47
  • The Match object
    04:15
  • Serialization
    06:09
  • Partial functions
    03:12
  • Code Introspection
    02:31
  • Map() Function
    09:59
  • Filter() Function
    03:02
  • Reduce() Function
    03:30

  • Python datetime Module
    04:32
  • Python datetime Module: Class Date
    03:20
  • Python datetime Module: Class Time
    02:25
  • Python datetime Module: Class Datetime
    05:42
  • Python datetime Module: Class Timedelta
    03:50
  • Python datetime Module: format dates and time
    04:46
  • Python datetime.strftime()
    06:16
  • Python datetime.strptime()
    02:48
  • Current date & time
    03:21
  • Get current time
    03:53
  • Timestamp to datetime
    02:46
  • Python time Module
    07:04
  • Python time.sleep() and multithreading
    08:10

Instructor

Daniele Protti
Project Manager and Software Architect
Daniele Protti
  • 3.9 Instructor Rating
  • 1,501 Reviews
  • 43,684 Students
  • 29 Courses

I have 20+ years experience in IT project management, software development and software architecture.

I have led several teams of software developers as project manager, quality manager and as team leader in different companies and different countries in sectors e.g. telecommunication, research & development, travel business, Internet marketing and Internet business, consultancy and services.

I have been responsible to collect the requirements of projects, applications and processes, design the databases and specify the final objects.

During my career I have accumulated a lot of experiences dealing with processes of any kind and the need to define the tools to manage them and collect the information.

Most of my tools have been written in VB, VBA, C++, C#, Java, PHP, Javascript using databases e.g. Informix, Postgres, Oracle and MySql.

I have organized all my experiences in courses which are not only a list of functions and methods but contain also my practical experiences and considerations about how to cope with the different situations and which solutions to suggest.

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